4 citations · 16 across the 19 of their papers we have counts for
5 papers · 1 filter
GenRec: Knowing Where to Reconstruct and Where to Generate
Ata Çelen, Jaewoo Jung, Federico Tombari +4
Generative novel view synthesis from sparse input images is rarely all reconstruction or all generation: pixels visible in some source view have a unique correct value modulated on…
PointDiT: Pixel-Space Diffusion for Monocular Geometry Estimation
Haofei Xu, Rundi Wu, Philipp Henzler +7
State-of-the-art single-image 3D reconstruction methods often rely on complex hybrid architectures and loss functions, or compress geometry into latent spaces in order to leverage…
AugSplat: Radiance Field-Informed Gaussian Splatting for Sparse-View Settings
Lorenzo Lazzaroni, Riccardo Bollati, Daniel Barath +2
Generating high-quality novel views at real-time frame rates remains a central challenge in 3D vision, particularly in sparse-view scenarios. Neural radiance fields have demonstrat…
DynaTok: Token-Based 4D Reconstruction from Partial Point Clouds
Weirong Chen, Keisuke Tateno, Hidenobu Matsuki +3
We address 4D reconstruction from partial point cloud sequences, where depth-sensor observations are incomplete, unordered, and lack explicit temporal correspondences. This geometr…
OpenGaFF: Open-Vocabulary Gaussian Feature Field with Codebook Attention
Kunyi Li, Michael Niemeyer, Sen Wang +3
Understanding open-vocabulary 3D scenes with Gaussian-based representations remains challenging due to fragmented and spatially inconsistent semantic predictions across multi-view…